It's kind of bizarre hearing your own accent again ... a friend recently returned to New Zealand told me she'd never realized how g**damn annoying the New Zealand accent was. And it's true. It's as annoying as hearing an American accent, when you're not used to one. Or an Australian accent, when you're not used to one. Or a British one, when you're not used to one. To say nothing of those nasal South Africans. I will let the Irish and Scots off this general indictment of accents ... digression ...
Anyway, another thing that was semi-bizarre was listening to the "Accommodation Guide" where people advertise for flatmates (roommates wanted). I hadn't really forgotten this, but it was still revealing to note the number of people advertising for flatmates of a specific gender. Here's the kicker, and the cultural exchange part. In New Zealand they're almost always advertising for a woman or a man to keep a flat mixed sex. In America they advertise for roommates to maintain a single sex household.
It was a rare student flat in New Zealand that was not mixed. Moreover, many (most?) of those mixed flatting situations were strangers. The prevailing attitude among the youth in New Zealand is (was, at least, five years ago) that (1) it's better to share a house with people you didn't previously know, and (2) you should have a mixture of men and women. What I've noticed in America is that these attitudes are almost precisely reversed—most people believe it's better to share housing with people of the same sex they already know.
There's two things going on there; gender and trust. Painting with [too?] broad a brush, Americans [Minnesotans] are still more conservative about gender. Notice how many women they elect to public office? Not so many.
There's also an issue of trust. New Zealand is still a small enough country that most of these potential flatmates you didn't know were probably known at two or three removes. But there is also a greater sense of trust in strangers that they won't turn out to be axe murderers or psycho killers. Or gun murderers, as seems to be more common in America. (Axes don't kill people. People kill people).
Interestingly enough, in New Zealand, a quintessential late-90s cult movie about the perils of flatting/house-sharing was Shallow Grave. Where one flatmate just died and left lots of cash behind. What does that say? Another movie about the perils of flatting was Scarfies (great soundtrack, by the way) where the risk in sharing a house was that you'd discover someone was growing dope in your basement, and your big moral dilemma was again, how to liquidate the windfall you'd come into.
Contrast that with the best American movie about room-mates: Single White Female. That would put you off living with other people.
The constant is that wherever you are, there are those awful accents to get used to. Except in Shallow Grave. They had nice Scottish accents.
The second best sporting event of the year is this weekend (the most important is from 9 June to 9 July). Good overview here of the current sad trend towards making cross country little more than a leafy green track race. It will also be good for World Cross to revert to its traditional one race format. For sure, the 12km format suits 10k runners more than it does milers, but there's no reason a well trained miler or 5km runner can't do quite well over cross country. John Walker was 4th at world cross in 1975, the same year he became the first man under 3:50 for the mile.
For "just" $19.95 you can watch the world cross country championships on the internet. So tempting ...
I've always been a little skeptical of the historical geography fascination with maps, as they seem to involve a lot of effort to generate description rather than analysis. Maps summarize averages well, but I've yet to see a good map that shows variation within the geographic units. No doubt it's possible with a little work ...
That said, people love pictures, especially people at conferences, so it seemed to be worth learning how to generate cool maps myself. Apparently there are ways to do maps in Excel, but why use Excel when you can use Stata? Here is the kind of stuff you can produce with the tmap package in Stata.
Black wives in the cotton south worked outside the home more than black wives elsewhere, and white wives anywhere ... something I knew already. But interesting to see in that form nevertheless. I could see the same thing on a table, where I could sort the columns and see more precisely the rate of labor force participation in various areas. But it would be hard on a table—even one where I grouped the states in geographic areas—to see the cotton south like you can see it here.
Anyone who's ever taught American history and done "the map exercise" (getting students to identify the states) knows that the general level of awareness of where the states are is pretty low. You can bemoan that all you like. I know I did at the time, "I'm a freaking foreigner and I know where the states are!!" kind of thinking, but really ... that is not going to get you far. Why should people know exactly where all fifty states are. I'm not sure that that is useful knowledge in and of itself. It's possible that as part of a good liberal education people will end up knowing where all fifty states are, but maybe they won't. It's also quite likely that the ability to visualize something that specific and commit it to memory is not common.
So while I don't see a lot of analytic value in maps communication and presentation is always a part of academic work, and often a very important part. It's easy to begrudge the extra work in making your analysis understandable to an audience, but that is to begrudge part of the job. Good graphs and maps are easier to understand quickly. A good graph or map can convey dramatic differences more clearly. Tables are more precise, to be sure, but will they grab your attention? Not as quickly as the same dramatic trend on a graph. Or a startling geographic trend on a map.
They say you learn something every day. Here's some stuff I've learned already this week
Vin Lananna (Dartmouth, then Stanford, now Oregon running coach) profile in the Eugene Register Guard.
There are not a lot of international championship 1500m races that involve just two Africans, but the Commonwealth Games 1500m final is one of them. It is unfortunately in the middle of the night. It is doubly unfortunate that while TVNZ offers free streaming video of the Games ... it is only available to people actually in New Zealand and there are no public proxy servers that allow you to fool the TVNZ site into thinking you're in New Zealand.
Because of all the white people, and the four NCAA Division 1 alumni in the race, it is attracting more attention than any other event at the Commonwealth Games on the normally U.S.-centric letsrun.
The main contenders--based on personal bests, all set last year--are New Zealand's Nick Willis, Australia's Craig "Buster" Mottram, and Australia's Mark Fountain.
Start lists and results are here. I am hoping for a New Zealand sweep, but this is unlikely.
Update, 25 March: Mottram and Sullivan tangle and fall. 2 minute split at 800m must play into Willis' hands. Willis wins! Brannen takes the silver. Fountain the bronze. Hamblyn (NZL) just 0.05 out of third. Sullivan and Mottram get 7th and 9th respectively.
From a telephone sampling of more than 2,000 households, university researchers found that Americans rate atheists below Muslims, recent immigrants, gays and lesbians and other minority groups in â€œsharing their vision of American society.â€? Atheists are also the minority group most Americans are least willing to allow their children to marry.
But I digress. I can't believe I've never repeated this story here on a slow news day. I found out the funny way about America's mystified reaction to atheists when I first arrived here, with several conversations that went like this ...
them: How you do pronounce your name?
me: Ee van. It's pronounced like in "evangelical"
them: So your name is Evangelical? What religion are you?
me: No, my name is Evan, and actually I'm an atheist.
them: An atheist??!! [WTF!!!???] How do you do that? What do you do on Sundays?
me: Well, it's quite easy really. You have more free time on Sundays for a start ...
... conversation rapidly degenerates as they realize I'm being flippant about the serious question of belief and non-belief
At this point I began searching for a new word that would cue people on the correct pronunciation of my name. I was not totally unaware that America was a little more religious than New Zealand; after all I had seen some statistics about the comparison. But I had no clue about how this all played out on an inter-personal level.
A friend of mine once said that many New Zealanders were not agnostics or atheists—they were apathists. They just didn't care about the question of whether there is a god or not, and what role god might play in the world. I think he's right. A lot of people (not all) in New Zealand are disinclined to think too hard and too long about that question. Atheism, like its counterpart, belief in God, is seen as thinking a little too hard about things. Like you were some kind of intellectual ... historically frowned upon in New Zealand.
These days I don't go round volunteering a belief in atheism, preferring to let my mind wander between atheism (yesterday), agnosticism (sometime last week), and apathism (most of the time, including today).
One of the most common ways people get to this lil' corner o' the internet is by searching about "coffee grounds." I'm guessing a lot of them are a little disappointed that I offer no composting tips. This post is for you. It is not for people who may think that coffee grounds offer insights into the future like tea leaves do.
Making coffee grounds for compost is easy. It's not quite as easy as falling off a log, but it's getting down there. The best results come from dry coffee grounds. I say this based only on intuition, rather than experiments.
Drip coffee machines with their paper filters tend to produce wet grounds that take a long time to dry out. Therefore, step one in getting good coffee grounds is to dump the Mr. Coffee machine ... You will get better (IMHO) coffee from this approach too.
The best grounds come from Italian-style stovetop espresso makers where the water is forced through the ground coffee. You can pick up a good Bialetti stovetop espresso maker for $25, comparable to your common and garden Mr. Coffee thing.
Once the espresso maker has cooled down, just unscrew it and tip the grounds into a little container. Nothing to it, right? Again, based only on intuition, I assert that saving up a litre-sized yogurt container's worth of grounds, and then scattering it on your compost pile is better than a little bit at a time.
Another easy way to get decent coffee grounds for compost is to use a Vietnamese coffee drip. These produce drier grounds than Mr. Coffee if you screw it down tightly. To get good grounds you should then take the screw off, and let the drip with the grounds in it sit out for a couple of days to dry before you dump the grounds into your little container.
A French press, while it produces decent enough coffee, does not produce great coffee grounds because of all the water swilling around in the bottom there.
Happy drinking and composting ...
The scenes in the REI spring 2006 catalog looked really familiar. On this page the words "See the world. Meet the locals .... Learn cool foreign phrases" didn't seem to fit the pictures. Oh yeah, that's the Kingston Flyer. That's Lake Wakatipu. New Zealand. Not foreign at all.
I've only been through six winters in Minnesota, and already the years when you got 60 inches of snow in a season are a memory. The last couple of winters have been pathetic. But this week has been great. Here's something you can show your kids in years to come! Remember when we had nearly a foot of snow on the ground ... When we had to shovel the sidewalk ... You young things don't know how tough it was back in the early years of the twenty first century ...
We even managed to snowshoe round Pike Island last night. It was glorious. But it seems to be a once in a season activity in the Twin Cities now.
Before I begin, let me note that this is not a knock on anyone in particular. I've subscribed to this myth in the past, and may in future succumb to the tendency again.
What I call the workout myth is the belief that afflicts all runners some of the time (and some runners all of the time, with a nod to Bob Dylan's Talkin' World War III Blues where I first heard this general phrase) that the way to improve is to drop some hard workouts into their week. 400s with short recovery, after not doing anything quickly for months. The qualification is crucial. Sometimes 400s with short recovery or long recovery are just the thing you need—I know I neglected them a little last year. The workout myth is this, that when you're unfit the way to get fitter quickly is to do some intervals.
As I say, I've done that. Here's my example of falling prey to the workout myth. After getting my weekly mileage up into the 70s in summer 2003, owing to the demands of travel and study my weekly mileage fell back to 30-50 for about six months. Sad story, weight increased, times went up. When I got back into it I threw myself into six weeks of winter base training moving the long run from 1:30 to 2:10 in 3 weeks, weekly mileage from 40 to 75 in a couple of weeks, and some "run to the barn" tempo runs. Good standard base building stuff, which I did because I know that "rule" about adding 10% a week to be too conservative. Then I had two weeks back at 50 miles, and my first race back was over 20km where I didn't run anything outstanding, but did run the same pace I'd been racing 5km at just two or three months earlier. Now, here's how the workout myth starts. I thought, "wow, that was decent with six weeks of base, what could I do if I did some speedwork?"
So I added some speedwork, VO2 max stuff like 8 x 3 minutes with 2 minute recoveries, and 15 x 1 minute with even recoveries. This was April/May in Minnesota where you know that you have the most ideal racing weather you're going to get until that 10 day stretch that surrounds the Twin Cities marathon. To accommodate the fatigue of doing this speedwork and trying to race at least every 2nd weekend the mileage stopped going up. It fell back into the 60s. It's not like I was racing well, relative to the benchmark I'd set at the 20km race I was doing worse every time.
I persisted with this foolery for a couple of months, before realizing what I was doing, put in three 75-85 mile weeks with only tempo runs, and was instantly rewarded with taking a minute off my season's best for 10km. Of course, the VO2 stuff was ultimately helpful, once I'd done the mileage. I was certainly doing better with my 60 miles and crappy workouts than I was with 35 miles and no workouts.
It's easy to fall into the workout myth, I did it just two short months after reading Lydiard. How quickly fools forget what they read. The workout myth is similar to the idea that you can spend money to advance a little quicker. The joy of running is that it's so simple, and that up to a point you can probably get the most out of your natural abilities by just going out and piling up the mileage. And in the miles you spend by yourself in that very simplicity you start to wonder if you couldn't get just a little better by doing something more complicated. More complicated, more structured must be better, no? Well, actually, no. Not all the time. Not to mention that workouts sound organized and precise, like you're more in control of your training. It's just not nearly as remarkable to say that your plans for the next 10 weeks are to gradually increase your mileage, and throw in some strides and fartlek when you feel good.
The other irony of adding in workouts is this, unless you fold them into a normal, everyday, training run out on the roads, trails and bikepaths they can be a lot more time consuming. All the time you spend driving to the track (if you have to), changing into spikes (if you want to), etc ... it all adds up to maybe 10 extra easy miles a week you could have run.
So, I hope that when I next am recovering from unfitness and get to that point after a few weeks of rebuilding the miles and think "What could I do if I added workouts?" that I pause and remember that the question should probably be "How long should I keep building my miles for?"
When I was a kid one of my favourite books was Richard Scarry's What Do People Do All Day?. (Another of my favorites was Snow White, I liked them so much that my father refused to repeat them more than once every couple of days by the time I was four)
Now that I look back at Richard Scarry, some gender stereotypes in there where Daddy goes out to work and Mommy consumes ("Mommy loved her new earrings .... Grocer Cat bought a new dress for Mommy. She earned it by taking such good care of the house") that maybe my parents didn't want me to read. But I digress. Slightly. Perhaps this interest in Richard Scarry was my initial foray into labo[u]r and economic history.
I am still interested in what do people do all day. But these days it is more of an academic interest, and at the end of the year I have a conference paper due on the topic. Specifically about what I learned from trying to classify and code half a million different occupations into something tractable enough for research. So here ends the fun discussion of childrens' books (with pictures!) and here begins some jottings towards a conference paper. Keep reading, it will be like a campfire sing-along ... with marshmallows at the end.
In all seriousness, I do this because just the thought that somebody who is not that interested in how to analyze occupations might read this is a useful discipline on my writing.
I think it's always useful to begin talking about "what do people do all day" with some [throat clearing] preliminaries about why it's an important topic. For better or worse, we all do a lot of work. Work affects everyone, and we should study things that affect large numbers of people. For now all the question about whether that is for pay, whether all that work is a good thing, or whether it could be done differently are to the side. They're important but should be distinguished from the descriptive task of measuring and classifying what people do all day.
What to classify: When we're talking about classifying work, it is conventional to divide it up into occupation—the tasks and duties people perform— industry— and what the American census calls "class of worker," loosely speaking what kind of authority a person has in their job; whether they're an employer directing others, an employee, or working by and for themselves.
These standard divisions are useful, and these days when we want to find out about them we normally ask the right questions to do so. I think it's important to keep in mind two caveats.
The first is that there is some correlation between these three variables which people take as natural and therefore conflate aspects of their job that researchers would like to distinguish. An example of this correlation and conflation is that some occupations are rarely found outside of certain industries. Farmers are never outside agriculture. But we cannot, conversely, carry this conflation forward. It is tempting to think that if we come across a nurse that he's working in health and medicine, but there are enough examples of nurses employed in manufacturing and education and elsewhere that we should pause before doing so. At the very least,
inferences guesses like this should be flagged in some way.
The second caveat is that the general public's appreciation of these distinctions between industry and occupation is not what social scientists would like it to me. For better or worse, people often have a clearer idea of what industry they (or their family members) are working in than precisely what they do. This caveat is probably somewhat related to the first one. It would be tempting to conclude that the general public should get with our academic program and understand this difference (or that we should study a different public) but regularities like this are interesting in their own right.
What I make of this observation that people tend to be clearer about industry than occupation are the following which I offer tentatively as hypotheses rather than definitive statements.
You can see this variety in what comes under the same occupational title by reading the modern responses to questions which aim to elicit the specific tasks people do. All farm laborers are not the same. Neither are all lawyers.
While there are regularities in what people in these occupations do they are not absolute. In casual conversation this probably doesn't matter too much, but for research it does matter. When we see "lawyer, in a law firm" that is as much as we know.
In short, ascribing characteristics to occupations is OK in social situations, but not so much in research. If we are going to ascribe something to an occupation—social status, for example—we should do it globally. Once we have classified all our data, we can re-classify it, simplify it, lump the professionals together, the clerks, the factory workers etc ...
Classification and coding. For the purposes of this discussion I take "classification" to be the somewhat abstract process of deciding what distinctions we are going to make between different responses (do we accept lawyer and attorney as the same job, for example), and "coding," the somewhat mechanical process of looking at a response (or group of responses) and typing a numeric code so that "criminal lawyer" and "defence lawyer" and "defending bad guys in court" all get code xxx and can be distinguished from lawyer's secretary and farmer.
As a practical matter I think that accuracy and consistency are enhanced by making distinctions by introducing new variables, rather than making longer codes. As I understand it, in the not so distant past disk space was a real concern and having one variable of three digits that combined two ideas was genuinely better than two variables of two digits that kept them separate. But these days disk space and memory is trivially cheap, so distinct ideas should be kept distinct.
One of the challenges with coding is to stick to the literal text, and only code that. This is another way of saying that we can't ascribe [too much] when coding. For example, if someone says they are a custodian we only know their occupation. It would be nice to know if they were are a school custodian or a hospital custodian, but we don't know that.
As I mentioned, I have coded nearly half a million occupations in the space of a couple of years (with some help). How do you do that? As I noted above occupation and industry are correlated. There are a lot of farmers who work in agriculture. A lot of teachers who work in education. For responses like these it is most efficient to code occupation and industry at the same time. In other situations, particularly manufacturing workers, there is some dependence of occupation on industry but not as much. Often it was more efficient to code a group of industries together, based on keywords (specific products such as "cotton" or "timber", or descriptions of types of workplaces, such as "shop" or "mill" or "plant"), and then code the occupations based on keywords that distinguished tasks, or rough gradations in skill or authority.
It is not uncommon that when actually doing the coding, other distinctions or classifications that might be useful occur to us. For example, we might find that lawyers are unusually forthcoming on whether they are criminal or corporate lawyers. Rather than revising the coding scheme post hoc to incorporate this distinction it is better to flag the cases we want to retain extra information on, and revisit them once the first round of coding is complete.
An important choice in coding is whether to lump or split? Should we assume that "attorneys" and "lawyers" are the same, that "merchants" and "dealers" are the same? That a "sales clerk" and a "saleslady" are the same. Those are ones I can accept. But what about a "hammerman" and a "blacksmith"? Trickier. It does depend on the amount of data, and the time it takes to recode. In general, people making codes that others will use should probably err on the side of splitting rather than lumping. It is easy enough to lump later on to get a tractable number of categories for analysis, but discovering that apparently disparate groups have been lumped together is more frustrating.
These are [unfinished] reflections from the trenches, or just coming out of the trenches, of actually coding lots of data. What strikes me in looking at work across time in censuses and surveys, is not the change but the stasis, at least in terminology. Despite changes in technology and who is working, many of the terms we use to describe work today existed back then. There are, of course, new occupations that did not exist in 1880 or 1900. Aviation and computer programming probably the most obvious. But look at the terms we use to describe occupations in aviation. Pilot and Captain. Straight out of the maritime industry.
In other words, the language of occupations has not really changed much, despite what we know from closer studies of the workplace that what some occupations do has changed. Coding and classifying surveys of work can only be a starting point, a description and analysis of context, in the collective project of understanding what people do all day.
Let me just note for posterity that this message drives me batty.
I think I remember that in Windows 3.1 and Windows 95 that you could do this. Why it's not possible in later, otherwise more advanced versions, of Windows, I don't know. And it's possible in the Macintosh version of Microsoft Office. I cannot be—I know I am not—the only person in the world who regularly works—nay, tries to work— on documents with the same structure, function and thus name in related projects who would like this to be possible.
Baseball lacks the same drama of the chase as cricket, and the truly great baseball purist's games are the ones dominated by pitchers, but I'll try to translate the significance of a score like this. It's like having two opposing pitchers throw nearly perfect games, and then the game comes down to whether an out of form player can get an RBI from a full count on the last at-bat. Or if you prefer home run duels, this is like a game with several grand slams that is all tied up at the bottom of the 9th, and only won on the last at-bat. In other words, you'd be saying something stronger than "holy smoke" after watching a game like that ...
and coffee too.
As any baseball fan who has a desk job and colleagues within hearing distance will know, the advent of websites that allow you to monitor the box score of the game has allowed one to both work and follow the game all day long.
The same nifty service is available for cricket fan at cricinfo. Today I have been semi-enjoying New Zealand let the West Indies back into the first test. And then the scores stopped updating! What happened? The scoreboard was stuck at West Indies 160/5 (45.0 ov) for quite some time.
They still put stickers on your mail telling you that they've inspected it.
Labour History. A special issue with articles on Australian communists! Sent to a foreigner! That has to be suspicious. How do I tell Homeland Security I find the articles on teeny, ineffective communist parties the most boring part of labor history?
One of the other delights of a trip home to New Zealand was getting the opportunity to buy New Zealand music. Now, some of this purchasing was a little redundant since it's available in iTunes, but not all of it. Flipping through the CD racks has its own pleasures that are only complemented by iTunes' suggestions and search engine.
So, what's been on the CD player (on the iPod) since I returned?
Fat Freddy's Drop. Based on a True Story. Wellington reggae band who I'd heard one previous song from (on a 1998 compilation CD). That one song was enough to make me drop the money on a full album, and I have not been disappointed.
Bic Runga continues to impress with her new album, Birds. What an amazing voice. Unfortunately, only her 2002 album Beautiful Collision is available on iTunes. And there's something neat about a song called Election Night.
The Exponents' retrospective album, Sex and Agriculture was a bargain, a double CD for a single CD price. If I read the album cover notes correctly "Sex" is the well-known hits, and "Agriculture" the B-sides and rarities. The Exponents are probably still a better live band, summer concerts their forte, but the album shows that their range is more than summer rock appreciated after a couple of beers.
Rounding out the additions to the collection was More Nature, a compilation of someone's judgment of New Zealand's best music in the past five years. Not a dud amongst them, and nice to hear that the indie rock influence has been complemented by groups with a different sound.
(fast connection needed for optimal viewing ...)
Universal [single-payer] health care will be a long-time coming in America.
Matthew Yglesias has a good post on this matter today. It doesn't matter how good an idea single-payer health care is (it is a very good idea), there are lots of people making lots of money from the current system of health care financing in America. They will be quite happy to pay good money to defend the current system. This includes doctors, who in the United States, are better paid (overpaid? that would be a value judgment) relative to other professionals. I would trust doctors to design a health care system like I would trust a collision repair specialist to design an intersection.
Because doctors and other medical professionals are doing quite well under the current system, and because most people already see health care providers a lot, you could not feasibly reform American health care by paying doctors off to keep quiet about the changes in its funding. Let me back up a little here, and explain. There are problems with access to health insurance and health care, but it's a problem of 1/7 of the population lacking insurance and access to care, not the vast majority of the country. The rest of the country who have health insurance of some form (I'm not pretending that all health insurance is great, or that everyone can see the doctor as much as they want) on average see doctors quite a lot.
That is quite a different starting point for reforming health care than when single-payer health care was introduced in other western countries. Health care was a small part of the economy, and people didn't go to doctors or hospitals as much (partly because medicine was less effective). I'll give the example of New Zealand, because I'm familiar with it and it's a good example of the politics. New Zealand introduced single-payer health care in the 1930s (as in the U.S. it had been talked about for a long time). The British Medical Association (the professional association for doctors, they are now the NZMA) said it was implacably opposed to socialized medicine. Though they probably spelled it socialised. After the Labour government threatened to import hundreds of Jewish refugee doctors from Germany (you may discern the ironies here for yourself), and the government raised the per-consultation fee doctors would receive. And it turned out that opposition was not so implacable. Overall, doctors earned more from the socialised scheme because more people went to the doctor. Though as cartoonists of the time pointed out, many doctors resented that their golf handicaps went up as their time on the course went down. In short, when health care was a relatively smaller part of the economy and people didn't go to the doctor as much as they do now, it was easier to introduce large-scale changes in how you organized and financed health care.
This is a generalization that holds across other western countries. By and large the dominant features of the way health care is financed in most western countries date to before World War II. (Major exceptions that I can think of include Canada and Taiwan right now) I am limiting myself here to talking about health care financing and funding. There has been a recent vogue of reforming the ownership and organization of hospitals and clinics in many countries, but much smaller changes in the extent of public and private financing. Health care is now a large, mature part of all those economies—though smaller than in the United States—but the single-payer or social insurance financing systems were set up well in advance of recent increases in health care expenditure.
I think that you need to add this—health care is a more mature sector than it was in other countries when they introduced universal health care—to the long list of reasons why universal health care will be a long time coming in America, even with the best political strategy and conditions to get there.
Another cheater blog entry ...
New Zealand and Australia are officially obsessed with "biosecurity." It comes with having a lot of agricultural earnings and being islands. For example, Oscar-winning actress Hilary Swank was busted for bringing in an apple and orange from America without declaring them.
When you leave New Zealand they have lots of stern warnings about what not to bring home. Basically they give you the impression that to be on the safe side, don't bring back anything that was once alive in any form. Like wild rice. We saw this display about dangerous foreign agricultural [and cultural] items at Christchurch airport. What was particularly amusing was that one of the dangerous items not to bring home was Byerlys wild rice. This will only be semi-amusing if you're from the Twin Cities. Otherwise it will be even more dull.